Calculates the temporal SNR (tSNR) and signal fluctuation to noise ratio (SFNR) of a 4D NIFTI containing time series images. Scripts in this repository are for building a processing gear in Flywheel.
- Gear input:
- 4D NIFTI
- Gear configuration options:
- Mask threshold
- Number of discarded volumes
- Size of central ROI
- Gear outputs:
- tSNR map, SFNR map in NIFTI format
- Plot of the temporal drift of mean signal within ROI, plot of the temporal drift of center of mass, plot of Weisskoff analysis (radius of decorrelation)
- JSON file containing statistic results e.g. mean tSNR, SFNR in ROI
The script tsnr.py
can also be executed seperately to generate tSNR maps on 4D NIFTIs containing time series images:
python tsnr.py [-o OUTBASE] [-d DISCARD_VOL] [-f BET_FRAC] [-r ROI_SIZE] infile
Dependencies include AFNI, NumPy, SciPy, NiBabel.
Reference: Friedman and Glover, 2006, Report on a multicenter fMRI quality assurance protocol.